code: def forward_cpu(self, inputs):
      self.retain_inputs((0, 1))
      x, gy0 = inputs
      gy0 = gy0.reshape(-1, *((1,) * (x.ndim - 1)))
      gx = 2 * x * gy0
      return (gx,)
  
file_path: chainer/chainer/functions/math/batch_l2_norm_squared.py
imports: import six
  import chainer
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.functions.math import sum
  from chainer.utils import type_check
label_desc: Use image node_id 1 for calling the BatchL2NormSquaredGrad obj's underlying member method code with example usage: obj.forward_cpu(inputs) and returns: gx